Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables

The validity of value-added models (VAMs) of teacher effectiveness depends on the ability of the measures to isolate teachers’ contributions to their students’ achievement. Existing VAMs differ in key aspects of their empirical specifications, however, leaving policymakers with little clear guidance on what factors are important to include when constructing a fair model. We examine the sensitivity and precision of teacher value-added estimates obtained under model specifications that differ based on whether they include student-level background characteristics, peer-level background characteristics, and/or a double-lagged achievement score. We also test the sensitivity of teacher VAM estimates to two model variations that the literature has not previously evaluated. First, because the data available in some states or districts may only link students to teachers rather than linking students to specific classrooms, we test whether replacing classroom average peer characteristics with teacher-year level averages affects the VAM estimates. Second, we allow for variation in the relationship between current and lagged achievement scores based on student demographic characteristics. Using data from a northern state and a medium-sized, urban district in that state, we find that teacher estimates are highly correlated across model specifications. Nonetheless, differences in VAM specifications can affect the placement of teachers across performance categories. The lowest correlation we observed—0.909—implies that 26 percent of teachers who are ranked in the bottom quintile under one specification would be ranked above this quintile when a different set of control variables is used. Differences in VAM estimates are often systematically related to student characteristics: teachers in a district that serves a relatively large fraction of poor and minority students receive lower performance estimates when controls for student and peer demographic characteristics are excluded from the VAM.